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Iterative Area Seeded Region Growing for Multichannel Image Simplification

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Part of the Computational Imaging and Vision book series (CIVI,volume 30)

Abstract

Motivated by the unsuitability of the image extrema paradigm for processing multiphase or multichannel images, we propose a solution in the context of image simplification based on a combination of the flat zone and seeded region growing paradigms. Concepts and results are illustrated on satellite images.

Keywords

  • lambda flat zone
  • mathematical morphology
  • area filter

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References

  1. R. Adams and L. Bischof. Seeded region growing. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(6):641–647, 1994.

    CrossRef  Google Scholar 

  2. E. Breen and D. Monro. An evaluation of priority queues for mathematical morphology. In J. Serra and P. Soille, editors, Mathematical Morphology and its Applications to Image Processing, pages 249–256. Kluwer Academic Publishers, 1994.

    Google Scholar 

  3. J. Crespo, R. Schafer, J. Serra, C. Gratin, and F. Meyer. The flat zone approach: a general low-level region merging segmentation method. Signal Processing, 62(1):37–60, 1997.

    CrossRef  Google Scholar 

  4. A. Mehnert and P. Jackway. An improved seeded region growing. Pattern Recognition Letters, 18:1065–1071, 1997.

    CrossRef  Google Scholar 

  5. F. Meyer and P. Maragos. Nonlinear scale-space representation with morphological levelings. J. of Visual Communication and Image Representation, 11(3):245–265, 2000.

    CrossRef  Google Scholar 

  6. P. Salembier, L. Garrido, and D. Garcia. Auto-dual connected operators based on iterative merging algorithms. In H. Heijmans and J. Roerdink, editors, Mathematical Morphology and its Applications to Image and Signal Processing, volume 12 of Computational Imaging and Vision, pages 183–190, Dordrecht, 1998. Kluwer Academic Publishers.

    Google Scholar 

  7. P. Salembier and J. Serra. Flat zones filtering, connected operators, and filters by reconstruction. IEEE Transactions on Image Processing, 4(8):1153–1160, August 1995.

    CrossRef  Google Scholar 

  8. P. Soille. On the morphological processing of objects with varying local contrast Lecture Notes in Computer Science, 2886

    Google Scholar 

  9. P. Soille. Morphological Image Analysis: Principles and Applications. Springer-Verlag, Berlin Heidelberg New York, 2nd edition, 2003 [Reprinted with corrections in 2004]. See also http://ams.jrc.it/soille/book2ndprint

    Google Scholar 

  10. F. Zanoguera and F. Meyer. On the implementation of non-separable vector levelings. In H. Talbot and R. Beare, editors, Proceedings of VIth International Symposium on Mathematical Morphology, pages 369–377, Sydney, Australia, 2002. Commonwealth Scientific and Industrial Research Organisation.

    Google Scholar 

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© 2005 Springer

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Brunner, D., Soille, P. (2005). Iterative Area Seeded Region Growing for Multichannel Image Simplification. In: Ronse, C., Najman, L., Decencière, E. (eds) Mathematical Morphology: 40 Years On. Computational Imaging and Vision, vol 30. Springer, Dordrecht. https://doi.org/10.1007/1-4020-3443-1_36

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  • DOI: https://doi.org/10.1007/1-4020-3443-1_36

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-3442-8

  • Online ISBN: 978-1-4020-3443-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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